Evidence map›Paper›PMID 41346427›Full record

ArticleBiostatistics & epidemiology2025

Mean Cost and Cost-Effectiveness Ratios with Censored Data: a Tutorial and SAS

Eduard Poltavskiy, Dingning Liu, Shuai Chen, Heejung Bang, Hongwei Zhao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biostatistics & epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Meta-Analysis of Cost-Effectiveness.Statistics in medicine · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Eduard PoltavskiyIndependent researcher, Sacramento, CA, USA.ORCID 0000-0002-4052-8593
Dingning LiuGraduate Group of Biostatistics, Department of Statistics, University of California-Davis, Davis, CA, USA.
Shuai ChenGraduate Group of Biostatistics, Department of Statistics, University of California-Davis, Davis, CA, USA.
Heejung BangGraduate Group of Biostatistics, Department of Statistics, University of California-Davis, Davis, CA, USA.
Hongwei ZhaoDivision of Occupational and Environmental Health, School of Medicine, University of Utah, Salt Lake City, UT, USA.

Funding

UC Davis Clinical and Translational Science CenterUL1TR001860 · NCATS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI KENYON, NICHOLAS J., LYLES, COURTNEY REES · 2016 to 2025
$47.3M
NCATS NIH HHS UL1 TR001860
6 · The paper itself

Abstract

Censoring is an unignorable issue when analyzing survival data and/or medical cost data. Medical costs may be viewed as a type of survival data-in that they accrue over time until an endpoint such as death-or a 'mark' variable. Since Lin et al. (1997) and Mushlin et al. (1998) published landmark papers on this topic, censored cost data have been extensively studied. In this tutorial, we explain how to estimate mean cost and cost-effectiveness ratios, along with three examples under two different data scenarios: when only total cost data (so one observation per person) or longitudinal data (or cost history) are available. We also provide an updated literature review. SAS codes in the supplement could be useful to practitioners and data analysts.

Indexed as

censoringcustomer lifetime valuehealth economicsmark variablemedical costsurvival analysis

Identifiers

PMID41346427
PMCPMC12674633

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.